Contact centers, which typically are associated with human agents, are used to provide customer service and support. Increasingly, contact centers are geographically dispersed. For example, a single enterprise may have multiple contact centers at different locations across the globe. Managing such a geographically dispersed system is difficult, particularly as an administrator may be unaware of local conditions affecting performance at one contact center but not others.
Typically, a contact center is assigned to handle particular types of calls or contacts. The different calls or contacts can be sorted into queues to await service by contact center agents. In addition, different queues may be supported by different contact centers simultaneously. In order to determine the health or status of different contact centers, administrators typically have access to text based or tabular tools. Such tools can provide a snapshot of a contact center's performance. However, determining the health of a contact center from such information is not intuitive. In addition, such information may not be capable of depicting parameters that are affecting performance of a contact center that are not themselves internal to the contact center. For example, contact center performance can be affected by overloading or disruptions of communication channels linking a serviced area to the contact center. As another example, a contact center may be affected by local events, such as natural disasters or weather events. As still another example, a contact center may be presented with an exceptionally high load, and may therefore present extended caller wait times or other indications of poor performance, because another contact center is experiencing difficulties that prevent it from taking its share of contacts associated with a queue serviced by both contact centers. In these cases, it can be particularly difficult for an administrator to identify the cause of performance issues within the enterprise, and to take corrective action.